基于机器学习的文档级情感分析

Sentiment analysis or opinion mining aims at identifying viewpoints of reviews which is quite popular in several fields. For example, businessman wants to find out if customers like their products or not and recommend systems tend to recommend items which receives many positive reviews. This paper focuses on document level polarity classification problem. To do this job better, we (1) use un-labeled sentences to create a huge dataset where sentences are annotated as either subjective or not, and the dataset can further be used to train subjectivity detector, (2) create an extract of a given review which only contain subjective information by using graph-cut-based subjectivity detector.（3）Then we perform polarity classification algorithm on this extract which can achieve high precision.